
The Introduction to AI Agents and Agentic AI course is designed to give you a deep yet beginner-friendly understanding of one of the most transformative areas in modern Artificial Intelligence: AI agents.
From personal assistants and autonomous bots to multi-agent systems powering automation, research, and decision-making—AI agents are becoming the backbone of next-generation AI applications.
This course explains what AI agents are, how they work, how they are built, how they learn, and how they can be guided to perform tasks autonomously.
You’ll explore foundational concepts, advanced architectures, and practical implementation patterns used in the industry today.
By the end of this course, you will understand the lifecycle, behavior, architecture, and real-world applications of AI agents.
What makes an AI system an “agent”
How agents perceive, reason, decide, and act
Differences between traditional AI models and agentic systems
You will learn the core building blocks of AI agents, including:
Perception mechanisms
Memory systems
Reasoning and planning components
Tools, APIs, and environments
Autonomy vs. human oversight
Explore the full spectrum of agent designs:
Simple rule-based agents
Goal-based agents
Utility-based agents
Learning agents
Multi-agent systems
Autonomous agents with self-optimization
Learn how to shape agent behavior using:
Prompting and instruction techniques
Reward functions
Constraints, guardrails, and policies
Reinforcement learning principles
Human-in-the-loop training
A deep dive into modern agentic system design:
Reactive vs. deliberative agents
Planning agents
Hybrid architectures
Tool-using agents
Orchestration and control patterns
Memory and retrieval systems
You’ll discover how to:
Build simple and advanced agents
Connect agents to tools and APIs
Use frameworks like LangChain, AutoGen, CrewAI, or agentic libraries
Deploy agents in real environments
Evaluate and improve agent behavior
This course is suitable for any skill level—no advanced coding background required.
Beginners curious about AI agent behavior
AI enthusiasts exploring autonomy and decision-making
Developers wanting to build practical agentic applications
Business professionals or founders wanting to leverage automation
Students pursuing AI, machine learning, or robotics
Anyone interested in next-generation intelligent systems
Whether you’re new to AI or looking to level up your knowledge, this course will give you the foundation needed to build and understand agentic systems.
AI agents are the future of intelligent automation.
They go beyond static models and can reason, plan, interact with tools, make decisions, and operate autonomously.
Industries today are moving rapidly toward:
Autonomous customer service
Automated workflows
Research agents
Multi-agent collaboration hubs
Smart assistants and copilots
Robotic decision-making systems
Learning AI agents now positions you at the forefront of the fastest-growing AI trend.
This course is organized into 6 structured modules:
Understanding AI Agents
Essential Ingredients for Building AI Agents
Types of AI Agents (Simple to Complex)
Guiding and Teaching AI Agents
AI Agent Architecture Patterns
Implementing AI Agents in Practice
Each module includes easy explanations, practical examples, and real-world use cases to ensure you learn effectively.
You will be able to:
Explain core concepts of AI agents and agentic AI
Understand how modern AI systems operate autonomously
Identify and use common agent architecture patterns
Guide and instruct agents to perform tasks
Build basic AI agents and understand how to extend them
Apply your knowledge to real-world automation and AI projects
This course gives you the essential foundation needed to enter the world of autonomous intelligent systems.
Enrollments
Level
Time to Complete:
Lessons:
Certificate:
Yes
One-time for 1 person
The Introduction to AI Agents and Agentic AI course is designed to give you a deep yet beginner-friendly understanding of one of the most transformative areas in modern Artificial Intelligence: AI agents.
From personal assistants and autonomous bots to multi-agent systems powering automation, research, and decision-making—AI agents are becoming the backbone of next-generation AI applications.
This course explains what AI agents are, how they work, how they are built, how they learn, and how they can be guided to perform tasks autonomously.
You’ll explore foundational concepts, advanced architectures, and practical implementation patterns used in the industry today.
By the end of this course, you will understand the lifecycle, behavior, architecture, and real-world applications of AI agents.
What makes an AI system an “agent”
How agents perceive, reason, decide, and act
Differences between traditional AI models and agentic systems
You will learn the core building blocks of AI agents, including:
Perception mechanisms
Memory systems
Reasoning and planning components
Tools, APIs, and environments
Autonomy vs. human oversight
Explore the full spectrum of agent designs:
Simple rule-based agents
Goal-based agents
Utility-based agents
Learning agents
Multi-agent systems
Autonomous agents with self-optimization
Learn how to shape agent behavior using:
Prompting and instruction techniques
Reward functions
Constraints, guardrails, and policies
Reinforcement learning principles
Human-in-the-loop training
A deep dive into modern agentic system design:
Reactive vs. deliberative agents
Planning agents
Hybrid architectures
Tool-using agents
Orchestration and control patterns
Memory and retrieval systems
You’ll discover how to:
Build simple and advanced agents
Connect agents to tools and APIs
Use frameworks like LangChain, AutoGen, CrewAI, or agentic libraries
Deploy agents in real environments
Evaluate and improve agent behavior
This course is suitable for any skill level—no advanced coding background required.
Beginners curious about AI agent behavior
AI enthusiasts exploring autonomy and decision-making
Developers wanting to build practical agentic applications
Business professionals or founders wanting to leverage automation
Students pursuing AI, machine learning, or robotics
Anyone interested in next-generation intelligent systems
Whether you’re new to AI or looking to level up your knowledge, this course will give you the foundation needed to build and understand agentic systems.
AI agents are the future of intelligent automation.
They go beyond static models and can reason, plan, interact with tools, make decisions, and operate autonomously.
Industries today are moving rapidly toward:
Autonomous customer service
Automated workflows
Research agents
Multi-agent collaboration hubs
Smart assistants and copilots
Robotic decision-making systems
Learning AI agents now positions you at the forefront of the fastest-growing AI trend.
This course is organized into 6 structured modules:
Understanding AI Agents
Essential Ingredients for Building AI Agents
Types of AI Agents (Simple to Complex)
Guiding and Teaching AI Agents
AI Agent Architecture Patterns
Implementing AI Agents in Practice
Each module includes easy explanations, practical examples, and real-world use cases to ensure you learn effectively.
You will be able to:
Explain core concepts of AI agents and agentic AI
Understand how modern AI systems operate autonomously
Identify and use common agent architecture patterns
Guide and instruct agents to perform tasks
Build basic AI agents and understand how to extend them
Apply your knowledge to real-world automation and AI projects
This course gives you the essential foundation needed to enter the world of autonomous intelligent systems.
Lessons
Quizzes
Tasks
Resources
(Average)
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